Data Visualisation
This course is currently offered in collaboration with Creative Futures Academy (CFA). CFA is a ground-breaking partnership between: The National College of Art and Design, University College Dublin, and the Institute of Art, Design + Technology. Our tailored programmes and micro courses offer access to expertise and networks across the three leading creative institutions and our industry partners. Learn with us as we experiment, innovate and respond to change.
The course will use the data visualization application Tableau. In addition, the open source software environment R together with a number of its data visualization libraries including ggplot2, Plotly and the mapping library Leaflet will be used. No prior experience with Tableau or R will be assumed.
On successful completion of this course, you will be able to:
1. Identify and critically appraise the history of data visualisation, the work of key practitioners and the emerging themes and critical debates relating to a data-driven society.
2. Apply the grammar of graphics and appreciate its role in the design of appropriate visuals.
3. Create graphics that visualise data in one, two and higher dimensions using proprietary and open source software tools.
4. Explore the emerging role of geospatial analysis in data analysis and develop interactive map-based visualisations.
5. Appreciate the role of statistical reasoning in data analysis and develop surveillance models for visualising data collected over time.
This course is intended for students who:
• have successfully completed a primary degree at level 8 and are interested in learning more about the field of Data Visualisation, and/or
• may be working in a related field related to data science, information design or graphic design, and/or
• want to retrain or upskill in order to start a career the field of Data Visualisation.
Students may come from a range of backgrounds, with varying levels of prior design experience (e.g., computing, engineering, technology, business, marketing, design, creative arts, psychology, etc. graduates) for whom data visualisation is a key area of interest.
Subjects taught
What will I study?
Topics covered in this course include:
• The grammar of graphics
• Visualising data in one, two and higher dimensions.
• Geospatial visualisation
• Interactive visualisation
• Dashboard design and development
• Data visualisation using open source software e.g., R.
• Review of key concepts associated with statistical reasoning
• Creating surveillance models based on data collected over time
• Publishing content using an open source framework.
Entry requirements
Minimum Entry Requirements
An undergraduate qualification of 2nd Class Honours or higher at Honours Degree Level.
Those without this qualification may be considered provided they can demonstrate Honours Degree equivalence, which can be verified through the RPL (recognition of prior learning) process. Typically, RPL candidates should have professional experience of 2-3 years in Data Visualisation, Information Design, or a related field.
Are there any Equipment / Software Requirements?
Students should have access to a computer with a standard specification.
The application Tableau will be provided to students.
Application dates
How to apply:
E: postgradadmissions@iadt.ie
T: 01 239 4612
Application Deadline
2023 Applications are now open
IADT operates a rolling admissions policy for graduate taught courses, with decisions issued in 4 weeks after a submitted and complete application is received. An application is incomplete until you provide all required items on the checklist (including the application fee, if applicable).
Generally, courses will remain open to applications until all places are filled.
Duration
4 Full Days on campus (10am - 4pm)
16th and 23rd September 2023
7th and 14th October 2023
Post Course Info
Future Careers
Successful graduates will be equipped with the knowledge, skills and competencies to work across a wide range of data visualisation projects and roles in any industry that is reliant on working with and understanding data, such as: technology (big data / data science); news and media, finance, biotech, government; etc. Graduates will gain real-world experience through the Professional Practice module that will prepare them for their future careers.
Upon completion of the programme graduates will also be positioned to pursue further study pathways, e.g. at Masters or PhD level.